1. Field
This disclosure relates generally to wireless communication systems and, more specifically, to techniques for frequency-domain joint detection in wireless communication systems.
2. Related Art
To increase capacity and performance of wireless communication systems that employ time division-synchronous code division multiple access (TD-SCDMA) techniques, a base station (BS) receiver may employ joint (multiple user) detection. Joint detection is similar to solving a least squares (LS) problem, which may represent a significant computational effort due to the amount of data that may be involved. In general, joint detection combines knowledge about all subscriber stations (SSs) that are active in one burst in a relatively large system of equations. This knowledge has included channel impulse responses (that have been estimated from training sequences), spreading codes, and received antenna samples. Typically, designers have attempted to develop algorithms that lower computational complexity associated with joint detection without significantly degrading joint detection performance. Traditionally, joint detection has been performed using time-domain approaches (in contrast to frequency-domain approaches), due to the lower complexity traditionally associated with time-domain approaches.
At least one known joint detection frequency-domain approach has attempted to reduce computational complexity associated with joint detection by employing an algorithm that is based on extending a system matrix of a least squares (LS) problem to a block circulant matrix that is then block diagonalized. As is known, a circulant matrix is a square matrix where each column has the same elements as the column to the left of it rotated down by one position. Due to the fact that Fourier vectors are eigenvectors of circulant matrix blocks, a system of equations whose defining matrix is circulant can be solved efficiently in the frequency-domain. The transformation to and from the frequency-domain can be done efficiently with fast Fourier transforms (FFTs), which can be extended to block-circulant systems. Similar to how circulant matrix blocks can be diagonalized by FFTs, block circulant matrix blocks can be block diagonalized by block FFTs.
According to this approach, a time-domain block circulant channel matrix has been converted to frequency-domain block diagonal channel matrix by using block FFTs. In a TD-CDMA system, K CDMA codes may be simultaneously active on the same frequency band and in the same time slot. For example, a TD-SCDMA system that is designed for eight simultaneous users may include eight (K=8) simultaneously active different CDMA codes. The different spreading codes facilitate signal separation at a receiver of a base station (BS). According to the required data rate, a given user might use several different CDMA codes and/or time slots. The transmission of one block of N data symbols can be modeled by a system of linear equations with a vector containing the received samples from all antennas, an unstructured matrix that contains knowledge about estimated channel impulse responses and spreading codes, and another vector that represents temporal and spatial noise. While joint detection in the frequency-domain may be performed with reduced computational complexity using FFTs, the computational complexity of the frequency-domain approach may still be relatively high and unacceptable for many applications.